Evidence map›Paper›PMID 16843168›Full record

ReviewJournal of the American College of Cardiology2006

Gene expression analysis of cardiovascular diseases: novel insights into biology and clinical applications.

David Seo, Geoffrey S Ginsburg, Pascal J Goldschmidt-Clermont

Open access · greenAbstract readReview
In one paragraph

Review in Journal of the American College of Cardiology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 66 citations in OpenAlex.

  1. Trial
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  11. The emerging role of microRNAs in drug responses.Current opinion in molecular therapeutics · 2010
    Review
  12. Genomic approaches to coronary artery disease.The Indian journal of medical research · 2010
    Review
  13. Article
  14. Article
  15. Article
  16. Secondary prevention strategies for coronary heart disease.Journal of thrombosis and thrombolysis · 2010
    Review
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

David SeoDivision of Cardiology, Department of Medicine and Center for Genomic Medicine, Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina 27710-0001, USA. david.seo@duke.edu
Geoffrey S Ginsburg
Pascal J Goldschmidt-Clermont
Center for Genomic Science · ITDuke Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the contribution of genetics to complex cardiovascular diseases such as atherosclerosis has been accepted for quite some time, full and detailed knowledge of the individual causative genes has been elusive. With the advent of genomic technologies and methods, the necessary tools are now available to begin pinpointing the genes that contribute to disease susceptibility and progression. One approach being applied extensively in candidate gene discovery is gene expression analysis of human and animal tissues using microarrays. The genes identified by these genomic studies provide valuable insight into disease biology and represent the initial steps toward the development of diagnostic tests and therapeutic strategies that will substantially improve human health. This paper highlights the progress that has been made in using gene expression analysis cardiovascular genomic research and the potential for applying these findings in clinical medicine.

Indexed as

AnimalsAtrial FibrillationCardiovascular DiseasesCoronary Artery DiseaseGene Expression ProfilingHeart FailureHeart TransplantationHumansHypertensionNeutrophilsOligonucleotide Array Sequence AnalysisPharmacogeneticsPolymorphism, Single Nucleotide

Identifiers

PMID16843168
PMCPMC7126828
OpenAlexW102401861

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.